1 Information Technology & Information Sharing in Supply Chains Zhi-Long Chen Michael O. Ball Robert H. Smith School of Business University of Maryland College Park, MD 20742

2 Supply Chain Management as a Competitive Weapon It is becoming more difficult for companies to compete on cost or even product quality  to seek new competitive advantages, companies are looking to innovative supply chains that can provide: –New levels of customer service especially in terms of order promising response and reliability –Greater product variety – extreme case customizable products –Fast introduction of new technologies –Fast introduction of new products  may need to quickly reconfigure supply chain including supply chain partners  Great burden on IT infrastructure.

3 Importance of Fast Access to Supply Chain Information order dist center availability factory availability local availability remote retail availability IT Infrastructure: provides “visibility” across global supply chain to allow search for product availability

4 Push and Pull Production Systems Order raw materials transport & storage Produce product Deliver product to customer/retailer transport & storage customer order Forecast demand Order raw materials transport & storage Produce product Deliver product to customer/retailer transport & storage customer order PUSH VS PULL

5 Push-Pull Systems product models Manufacturing incl final assembly suppliers generic products and components Manufacturin g Assembly to order Push-pull boundary inventory forecast driven order driven

6 Assemble-to-Order In an assemble-to-order (ATO) production environment, final product assembly is not carried out until a customer order is received. ATO Advantages: –Greater product variety –Fast integration of new technologies –Lower inventory costs Making it work requires sophisticated order promising and fulfillment systems

7 Order Promising Decision Support in an ATO Setting Capacity Availability Capacity Planning Aggregate Planning Master Production Scheduling (MPS) Material Requirements Planning (MRP) x Order promising in assemble-to-order environment: match available resources to customer orders Resources: raw material and component availability production capacity customer orders Order Promising Decisions: accept/reject/split order; order quantities and delivery dates Considerations: order profitability; customer priority; customer satisfaction (reducing response/delivery time); production efficiency

8 Decision Models + Flexible IT  Flexibility in Production Planning and Order Handling 4/54/64/74/84/9 promise date Factory 1 Factory 2 4/2 new orders promise date Factory 1 Factory 2 4/3 new orders promise date Factory 1 Factory 2 4/4 new orders Flexibility can substantially improve overall business performance but it is far from commonplace!!!

9 Information Technology Challenges Integration of business information systems: ERP, supply chain mgmt, etc. Inter-company communication (vital in today’s multi-company supply chains) Making sophisticated business systems available to small and medium-sized firms Non-technical challenges: –international regulatory and standards issues –balancing need to share with privacy needs

10 Phenomenon Observed in Supply Chain Order Size Time Customer Demand Customer Demand Retailer Orders Distributor Orders Production Plan

11 Bullwhip Effect The bullwhip effect is a phenomenon observed in supply chains wherein the demand variability increases as one moves upstream from retailers to distributors to manufacturers Retailers Warehouses/ Distributors Manufacturers

12 Bullwhip Effect Example: Bullwhip Effect Example: P&G Diapers

13 Bullwhip is Bad It distorts the order information & amplifies order variability. Impact of Bullwhip Effect: -- Inventory: More safety stock needed -- Customer Service: Lower service level, more likely to cause stockouts and lost sales -- Manufacturing: Lower capacity utilization -- Transportation: Lower utilization of transportation -- Warehousing: More warehouse capacity needed Higher costs

14 Root Causes: Lack of Information 1. Demand forecast updating 2. Rationing and shortage gaming Causes of Bullwhip Effect

15 Cause 1: Demand Forecast Updating (Demand Signal Processing) Retailers forecast customers demand and then place orders with manufacturer Manufacturer receives orders from retailers Orders from downstream in the past p time periods D t-p, D t-p +1, …, D t- 1 Order Q t goes to upstream CustomersMfctr. Lead time L Demand variability gets amplified from downstream to upstream! - Commonly, the variability of Q is 2 to 15 times the variability of D Retailers

16 Cause 2: Rationing and Shortage Gaming As a result, customers’ orders give the supplier little information on a product’s real demand, a particularly vexing problem for new products When product demand exceeds supply, a manufacturer often rations its product to customers. Example: Car Manufacturer Available = 200 Dealer 1 Dealer 2 Order = 100 Order = 200 Received = 67 Received = 133 Only 2/3 of the order can be fulfilled Need = 120 Need = 180 Order = 180 Order = 270 Knowing the manufacturer policy, customers exaggerate their real needs when they order (game the system). Example: Car Manufacturer Dealer 1 Dealer 2 Available = 500 Received = 180 Received = 270

17 Information Sharing to Counteract the Bullwhip Sharing sales and inventory data Allocation based on past sales 2. Shortage Gaming Use of point-of-sale (POS) data Electronic data interchange (EDI) Vendor-managed inventory Lead-time reduction 1. Demand Signal Processing InitiativesCause of Bullwhip

18 Famous Success Story: Benetton Benetton, the Italian sportswear manufacturer, was founded in In 1975, Benetton had 200 stores across Italy. Ten years later, the company expanded to the U.S., Japan and Eastern Europe. Sales in 1991 reached 2 trillion. Many attribute Benetton’s success to successful use of communication and information technologies in their supply chain.

19 Famous Success Story: Benetton 1. Integrated Information Systems Global EDI network that links agents with production and inventory information EDI order transmission to HQ EDI linkage with air carriers Data linked to manufacturing 2. Coordinated Planning Frequent review allows fast reaction Integrated distribution strategy

20 Information Sharing Challenges Build strategic partnerships between manufacturers, distributors, and retailers Develop effective collaborative demand forecasting methods Create effective mechanisms for information sharing across supply chain partners: –Technical issues Integrating incompatible systems standards –Business issues: incentives to share Overcoming privacy/proprietary information concerns